A grading system based on normal distribution principles uses a statistical approach to evaluate student performance. This method assumes that student scores will naturally fall along a bell-shaped curve, with the majority clustered around the average and fewer students achieving very high or very low scores. A specific tool, often digital, facilitates this process by allowing educators to input raw scores and then distributing grades based on the desired curve parameters, such as the mean and standard deviation.
Normal distribution grading can be useful in large classes where a wide range of abilities might be present or when seeking to ensure a consistent distribution of grades across multiple sections of the same course. It can help mitigate the impact of factors like test difficulty or subjective grading biases. However, it also raises concerns about potential unfairness if the class doesn’t truly adhere to a normal distribution or if it discourages collaboration and creates an overly competitive environment. The concept stems from the field of statistics and its application to education has been debated for decades.
